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This paper is concerned with nonzero-sum discrete-time stochastic games in Borel state and action spaces under the expected discounted payoff criterion. The payoff function can be unbounded. The transition probability is a convex combination of finite probability measures that are dominated by a probability measure on the state space and depend on the state variable. Under suitable conditions, the authors establish the existence of stationary almost Markov ε-equilibria and give an approximation method via some stochastic games with bounded payoffs. Finally, a production game is introduced to illustrate the applications of the main result, which generalizes the bounded payoff case. [ABSTRACT FROM AUTHOR]

Crowding, a fundamental limit in object recognition, is believed to result from excessive integration of nearby items in peripheral vision. To understand its pooling mechanisms, we measured subjects’ internal response distributions in an orientation crowding task. Contrary to the prediction of an averaging model, we observed a pattern suggesting that the perceptual judgement is made based on choosing the largest response across the noise-perturbed items. A model featuring first-stage averaging and second-stage signed-max operation predicts the diverse errors made by human observers under various signal strength levels. These findings suggest that different rules operate to resolve the bottleneck at early and high-level stages of visual processing, implementing a combination of linear and nonlinear pooling strategies. [ABSTRACT FROM AUTHOR]